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1NsDaiyjpAYdpGBx5hwdckYJNPcQa6Rn4s

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Godel's ACTUAL Proof ☺

  1. (∃x)Dem(x, z) means there is a proof with Gödel Number x which demonstrates z or more simply z is demonstrable
  2. ~ (∃x) Dem(x, z) means z is not demonstrable
  3. A specific case of this expression is obtained by swapping z by Sub(y, 17, y)
  4. We get ~ (∃x) Dem(x, Sub(y, 17, y)) - lets call this formula B
  5. B means: the formula with Gödel number Sub(y, 17, y) is not demonstrable
  6. Lets call the Gödel number of B: n
  7. Lets replace all instances of the variable y with n to get ~ (∃x) Dem(x, Sub(n, 17, n)) – lets call this formula G with a
    Gödel number of g
  8. G means: the formula with Gödel number Sub(n, 17, n) is not demonstrable
  9. But Sub(n, 17, n) is what we did on line 7 therefore Sub(n, 17, n) has a Gödel number of g
  10. Therefore, G means: the formula with Gödel number g is not demonstrable
  11. Gödel proved that G is demonstrable if and only if ~G is demonstrable
  12. But if the calculus is to be consistent, then G can never be demonstrable otherwise there would be inconsistencies as
    its formal negation must also be demonstrable
  13. Since G and its negation ~G are tautological (they are the only 2 options so one must be true) either G is true or ~G is
    true.
  14. It is easy to see that G is true as it states that ‘G is not demonstrable’ which we have just proved to be the case if the
    calculus is to be consistent
  15. Therefore G is true and can not be demonstrated. Therefore the calculus is incomplete
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genetic algorithm

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Utilizing K and S combinators of the Combinatory logic, logical functions can be represented in as functions of combinators:

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Forth is the ultimate language for building extensions. Programming in Forth is generating higher levels of abstractions, until you have a language well fitted to solve your problem. The simplicity of the underlying system allows it to rely on it

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Forth is the best language. I'm pleased at its success, especially in the ultra-conservative arena of Artificial Intelligence. I'm disturbed that people who should, don't appreciate how it embodies their own description of the ideal programming language.

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Threaded-code changed the structure words (such as DO LOOP IF THEN ). They acquired an elegant implementation with addresses on the data stack during compilation.
It uses post-fix op-codes and composes addresses on the data stack, .

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I have found Forth to be outstanding for mathematical & scientific programming, for simulation, and for embedded programming of microcontrollers. It is ideal for experimenting with data structures. It combines low level thinking and high level design,

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you know when your stack is too long because you start stack juggling rot, swap, -rot, over,. factor, simplify, and if you really need three arguments, one of them is slowly varying parameter and can be kept in a variable removing the stack juggling noise.

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If you have a lot of small definitions you are writing Forth. In order to write a lot of small definitions you have to have a stack
Forth = Definitions + Stacks
But the definitions can accept parameters
There is something more than the formalism and syntax

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When you devised an application you wrote a hundred words or so that discussed the application and you used those hundred words to write a one line definition to solve the application. It is not easy to find those hundred words, but they exist,

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When dealing with binary numbers and flags, it is often useful make comparison tests such as "Are n1 and n2 both positive?" and "Are either n1 or n2 not true?"
A bit is a single boolean number, 1 or 0. A byte is currently defined as 8 bits.

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Predicate calculus is a formal language for expressing statements that are built from atomic formulas. Atomic formulas can be constants, variables, functions, and predicates.

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The perceptron is the computational workhorse in this system. In this it is reasonable to model the selected risk factors for the system and calculate a base risk that is trained and updated over time.

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A response based on current data coupled with expected future data, a prior data, and external systems data processed at this level would feed into an output layer. The result of the neural network would supply the output as an economic risk function.

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The data from multiple organisations can be fed into a decentralised system that can be distributed to all users. This could be integrated and sold as a product enhancement by existing vendors or independent third parties could maintain external data-sets.